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A hybrid modeling framework to support economic valuation studies on aquatic biotic condition
Citation:
Fergus, Carol, K. Swedberg, Jacqueline Brooks, J. Corona, A. Herlihy, R. Hill, P. Kaufmann, R. Mitchell, AND P. Ringold. A hybrid modeling framework to support economic valuation studies on aquatic biotic condition. American Geophysical Union Annual Meeting, San Francisco, CA, December 11 - 15, 2023.
Impact/Purpose:
Quantifying the total economic value of water quality regulatory actions on aquatic resources can be challenging because it requires estimating non-use (existence) value, which can be subjective and difficult to quantify. Existence value is characterized as the satisfaction people derive knowing that a resource exists even though they may never use it. It is rarely integrated into economic valuation studies, and as a result, the value people place on environmental quality may be significantly underestimated. The U.S. EPA is conducting a national stated preference study that in part seeks to quantify the existence portion of total economic value of water quality policies across the conterminous U.S. (CONUS). Previous work identified appropriate biological indicators that can capture existence values to integrate into the stated preference survey. To support this work, we propose developing a hybrid modeling framework to assess how regulatory actions affect aquatic biological integrity through changes in environmental conditions. The hybrid framework will combine scenario-modeling capabilities of HAWQS (Hydrologic and Water Quality Systems modeling system) with the biological and ecological insights of structural equation models and the National Aquatic Resource Surveys. This synergy will expand the capabilities of the individual models to be able to explore management scenario outcomes on aquatic biological integrity. The proposed framework will provide important insights into the connections among policy and environmental condition and offers promise as a tool to explore future climate scenarios.
Description:
The U.S. Environmental Protection Agency (EPA) is conducting a national stated preference study that aims to quantify the total economic value (human use and existence value) of water quality policies across the conterminous US (CONUS). Previous work identified the ratio of observed-to-expected (O/E) taxonomic richness of macroinvertebrates as a biological condition indicator that captures existence value of aquatic ecosystems. Predictive models are needed to connect candidate management options to changes in macroinvertebrate O/E to support the valuation study objectives linking policy to aquatic biological response. We developed structural equation models (SEM) with the EPA National Aquatic Resource Surveys (NARS) data to predict macroinvertebrate O/E in Western U.S. streams (n = 595 sites). We found that land use activities decreased O/E through pathways associated with degraded water quality (increased total nitrogen) and increased fine, unstable stream sediments. However, specific management practices and effects on aquatic ecosystem condition could not be evaluated using the NARS-SEM approach with landscape-level data. The Hydrologic and Water Quality System (HAWQS) is a process-based watershed modeling system used to predict effects of various management scenarios (e.g., riparian buffers, green infrastructure) on water quality, but HAWQS has data constraints limiting applications at national extents and predicting biological responses. We propose developing a hybrid modeling framework that combines the mechanistic features from HAWQS with the ecological features from NARS-SEM. We discuss the challenges of bringing together two modeling approaches that operate at different spatial and temporal scales and have distinct data requirements. We outline considerations and caveats to implementing the HAWQS-SEM framework such as tradeoffs in spatial extent and model performance. The HAWQS-SEM framework is a promising analytic approach that can explore how specific management activities and future climate scenarios may affect aquatic ecosystem condition, which will be critical to support policy and management decisions. The views expressed in this abstract are those of the author(s) and do not necessarily represent the views or policies of the U.S. Environmental Protection Agency.